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2024 CSAA/IET International Conference on Aircraft Utility systems, AUS 2024

作者： Yang, Hongji Xia, Tianxiang He, Jincheng AVIC Nanjing Engineering Institute of Aircraft System Nanjing China Aviation Science and Technology Key Laboratory of Aviation Mechanical and Electrical System Nanjing China Nanjing Vocational-University of lndustry-Technology Nanjing China

Dynamic load identification is a crucial aspect in the field of structural dynamics. In recent years, the identification method based on the Least Squares Support Vector Machine (LSSVM) has garnered significant attention. The LSSVM method offers high accuracy, does not require extensive response information, and exhibits strong algorithmic stability, meaning the load identification results remain consistent across different training sessions with the same training and prediction sets, without cumulative error. However, research on identification using this method is still in its infancy, with many issues yet to be addressed. This paper investigates the adaptability of this method, exploring the effects of factors such as the position of sinusoidal excitation, amplitude, frequency, and load type on the identification results. The computational results indicate that the dynamic load identification method based on the least squares approach has strong adaptability and holds certain value for engineering applications. © The Institution of engineering & technology 2024.

关键词： Dynamic loads

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Learning Fine-Grained information with Capsule-Wise Attention for Salient Object Detection

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IEEE Transactions on Multimedia 2023年 1-14页

作者： Zhao, Sanyuan Wen, Zongzheng Qi, Qi Lam, Kin-Man Shen, Jianbing School of Computer Science & Technology Beijing Institute of Technology China Department of Electronic and Information Engineering The Hong Kong Polytechnic University Hong Kong State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science University of Macau Macau China

With the popularity of convolutional neural networks being used for salient object detection (SOD), the performance has been significantly improved. However, how to integrate crucial features for modeling salient objects needs further exploration. In this work, we propose an effective feature selection scheme to solve this task. Firstly, we provide a Simplified Atrous Spatial Pyramid Pooling (SASPP) module to lightweight the multi-scale features. Dealing with the SASSP features, we design a pixel-level local feature selection scheme named Multi-Scale Capsule-wise Attention (MSCA). It aggregates features from multi-scales by dynamic routing and helps the network to generate fine-grained prediction maps. In addition, we exploit holistic features by the Spatial-wise Attention and Channel-wise Attention (SA/CA) mechanisms, which adaptively extracts spatial or channel information. We also propose a Multi-crossed Layer Connections (MLC) structure in the upsampling stage, to fuse features from not only different levels but also different scales. The salient object prediction is performed in a coarse-to-fine manner. By conducting comprehensive experiments on five benchmark datasets, our method achieves the best performance when compared to existing state-of-the-art approaches. IEEE

关键词： Object detection

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A Survey of Human-machine Collaboration in Fuzzing 7

A Survey of Human-machine Collaboration in Fuzzing

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7th IEEE International Conference on Data science in Cyberspace, DSC 2022

作者： Yan, Qian Huang, Minhuan Cao, Huayang National Key Laboratory of Science and Technology on Information System Security Beijing China

ISBN: (数字)9781665474801

ISBN: (纸本)9781665474801

Security vulnerabilities are a major threat to network security, and fuzzing is one of the most widely used vulnerability mining techniques. Traditional fuzzing consists of three phases, where security experts perform pre-processing manually, then drive the fuzzers to perform testing, and finally manually inspect the test results to uncover and analyse potential flaws in software. In recent years, with the proposal of various semi-automatic and automated techniques, the efficiency of vulnerability mining has increased significantly. However, in the midst of researchers' efforts to improve the efficiency of fuzzing, the role played by humans in this process has gradually been overlooked. Complete fuzzing is a joint human-machine process. In this paper, we review existing work on fuzzing from the perspective of human-machine collaboration, to help researchers understand the role played by humans and the importance of human-machine collaboration in the fuzzing process. First, we introduce the concept of fuzzing and the framework of human-machine collaboration. We then propose to classify fuzzing based on human-machine collaboration into three classifications based on the role of humans in the testing session: human-out-of-the-loop, human-on-the-loop, and human-in-the-loop. Using these classifications, we discuss and summarise the main techniques and methods used in the testing sessions. Finally, we provide future research directions for fuzzing. © 2022 IEEE.

关键词： Network security

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A Novel Pipelining Encryption Hardware system with High Throughput and High Integration for 5G

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China Communications 2022年第6期19卷 1-10页

作者： Yuntao Liu Zesheng Shen Shuo Fang Yun Wang College of Information and Communication Engineering Harbin Engineering UniversityHarbin 150001China Key Laboratory of Advanced Marine Communication and Information Technology Ministry of Industry and Information TechnologyHarbin 150001China Guangdong Greater Bay Area Institute of Integrated Circuit and System Guangzhou 510535China

This paper presents a ZUC-256 stream cipher algorithm hardware system in order to prevent the advanced security threats for 5 G wireless *** main innovation of the hardware system is that a six-stage pipeline scheme comprised of initialization and work stage is employed to enhance the solving speed of the critical logical ***,the pipeline scheme adopts a novel optimized hardware structure to fast complete the Mod(231-1)*** function of the hardware system has been validated experimentally in *** hardware system shows great *** with the same type system in recent literatures,the logic delay reduces by 47%with an additional hardware resources of only 4 multiplexers,the throughput rate reaches 5.26 Gbps and yields at least 45%better performance,the throughput rate per unit area increases 14.8%.The hardware system provides a faster and safer encryption module for the 5G wireless network.

关键词： encryption hardware system for 5G ZUC-256 stream cipher algorithm pipeline scheme throughput rate integration rate

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In-Vehicle Network Injection Attacks Detection Based on Feature Selection and Classification

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Automotive Innovation 2024年第1期7卷 138-149页

作者： Haojie Ji Liyong Wang Hongmao Qin Yinghui Wang Junjie Zhang Biao Chen Key Laboratory of Modern Measurement and Control Technology Ministry of EducationBeijing Information Science and Technology UniversityBeijing 100192China State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body College of Mechanical and Vehicle EngineeringHunan UniversityChangsha 410082China School of Transportation Science and Engineering Beihang UniversityBeijing 100191China Hefei Innovation Research Institute Beihang UniversityHefei 230012China

Detecting abnormal data generated from cyberattacks has emerged as a crucial approach for identifying security threats within in-vehicle *** transmission of information through in-vehicle networks needs to follow specific data for-mats and communication protocols ***,statistical algorithms are employed to learn these variation rules and facilitate the identification of abnormal ***,the effectiveness of anomaly detection outcomes often falls short when confronted with highly deceptive in-vehicle network *** this study,seven representative classification algorithms are selected to detect common in-vehicle network attacks,and a comparative analysis is employed to identify the most suitable and favorable detection *** consideration of the communication protocol characteristics of in-vehicle networks,an optimal convolutional neural network(CNN)detection algorithm is proposed that uses data field characteristics and classifier selection,and its comprehensive performance is *** addition,the concept of Hamming distance between two adjacent packets within the in-vehicle network is introduced,enabling the proposal of an enhanced CNN algorithm that achieves robust detection of challenging-to-identify abnormal *** paper also presents the proposed CNN classifica-tion algorithm that effectively addresses the issue of high false negative rate(FNR)in abnormal data detection based on the timestamp feature of data *** experimental results validate the efficacy of the proposed abnormal data detection algorithm,highlighting its strong detection performance and its potential to provide an effective solution for safeguarding the security of in-vehicle network information.

关键词： Classification algorithm Anomaly detection In-vehicle network Feature extraction Injecting attack

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Edge-aware Feature Aggregation Network for Polyp Segmentation

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Machine Intelligence Research 2025年第1期22卷 101-116页

作者： Tao Zhou Yizhe Zhang Geng Chen Yi Zhou Ye Wu Deng-Ping Fan PCA Lab Key Laboratory of Intelligent Perception and Systems for High-dimensional Information of Ministry of EducationSchool of Computer Science and EngineeringNanjing University of Science and TechnologyNanjing210094China School of Computer Science and Engineering Northwestern Polytechnical University(NPU)Xi’an710129China School of Computer Science and Engineering Southeast UniversityNanjing211189China Computer Vision Lab ETH ZürichZürich8092Switzerland

Precise polyp segmentation is vital for the early diagnosis and prevention of colorectal cancer(CRC)in clinical ***,due to scale variation and blurry polyp boundaries,it is still a challenging task to achieve satisfactory segmentation performance with different scales and *** this study,we present a novel edge-aware feature aggregation network(EFA-Net)for polyp segmentation,which can fully make use of cross-level and multi-scale features to enhance the performance of polyp ***,we first present an edge-aware guidance module(EGM)to combine the low-level features with the high-level features to learn an edge-enhanced feature,which is incorporated into each decoder unit using a layer-by-layer ***,a scale-aware convolution module(SCM)is proposed to learn scale-aware features by using dilated convolutions with different ratios,in order to effectively deal with scale ***,a cross-level fusion module(CFM)is proposed to effectively integrate the cross-level features,which can exploit the local and global contextual ***,the outputs of CFMs are adaptively weighted by using the learned edge-aware feature,which are then used to produce multiple side-out segmentation *** results on five widely adopted colonoscopy datasets show that our EFA-Net outperforms state-of-the-art polyp segmentation methods in terms of generalization and *** implementation code and segmentation maps will be publicly at https://***/taozh2017/EFANet.

关键词： Colorectal cancer polyp segmentation edge-aware guidance module scale-aware convolution module cross-level fusion module

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Plasmon coupling-driven enhanced high-order multiphoton excited fluorescent performance of metal-organic frameworks

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Nano Research 2024年第7期17卷 6502-6508页

作者： Tong Meng Bo Li Linlin Zeng Xianshun Sun Yupeng Tian Hongping Zhou Meng Zhou Dandan Li Institutes of Physical Science and Information Technology Key Laboratory of Structure and Functional Regulation of Hybrid MaterialsMinistry of EducationAnhui UniversityHefei 230601China School of Chemistry and Chemical Engineering Anhui UniversityHefei 230601China Hefei National Research Center for Physical Sciences at the Microscale University of Science and Technology of ChinaHefei 230026China

Accessing high-order multiphoton excited fluorescence(H-MPEF)materials is challenging yet and needs complicated synthesis *** this study,we successfully assembled plasmonic Au nanorods(Au NRs)with multiphoton responsive metalorganic frameworks(MOFs),resulting in a significant several-fold enhancement of *** extent of multiphoton enhancement was found to be strongly dependent on the degree of overlap between the multiphoton excitation wavelength of MOFs and the localized surface plasmon resonance absorbance of Au NRs,indicating the importance of plasmon-induced resonance energy ***,plasmon-induced hot electron transfer played a vital role in enhanced multiphoton activity as ***,the optimum H-MPEF enhancement occurs at the second near-infrared(NIR-II)region,which provides a promising platform for fluorescent *** findings provide a feasible and practical method to fabricate optimized H-MPEF materials for biological imaging using tissue-penetrating NIR-II light.

关键词： metal-organic framework(MOF) plasmon resonance multiphoton activity fluorescence imaging

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FCOS-LSC:A Novel Model for Green Fruit Detection in a Complex Orchard Environment

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Plant Phenomics 2023年第3期5卷 546-563页

作者： Ruina Zhao Yujie Guan Yuqi Lu Ze Ji Xiang Yin Weikuan Jia School of Information Science and Engineering Shandong Normal UniversityJinan 250358China School of Engineering Cardiff UniversityCardiff CF243AAUK School of Agricultural Engineering and Food Science Shandong University of TechnologyZibo 255000China Key Laboratory of Facility Agriculture Measurement and Control Technology and Equipment of Machinery Industry Zhenjiang 212013China

To better address the difficulties in designing green fruit recognition techniques in machine vision systems,a new fruit detection model is *** model is an optimization of the FCOS(full convolution one-stage object detection)algorithm,incorporating LSC(level scales,spaces,channels)attention blocks in the network structure,and named *** method achieves efficient recognition and localization of green fruit images affected by overlapping occlusions,lighting conditions,and capture ***,the improved feature extraction network ResNet50 with added deformable convolution is used to fully extract green fruit feature *** feature pyramid network(FPN)is employed to fully fuse low-level detail information and high-level semantic information in a cross-connected and top-down connected ***,the attention mechanisms are added to each of the 3 dimensions of scale,space(including the height and width of the feature map),and channel of the generated multiscale feature map to improve the feature perception capability of the ***,the classification and regression subnetworks of the model are applied to predict the fruit category and bounding *** the classification branch,a new positive and negative sample selection strategy is applied to better distinguish supervised signals by designing weights in the loss function to achieve more accurate fruit *** proposed FCOS-LSC model has 38.65M parameters,38.72G floating point operations,and mean average precision of 63.0%and 75.2%for detecting green apples and green persimmons,*** summary,FCOS-LSC outperforms the state-of-the-art models in terms of precision and complexity to meet the accurate and efficient requirements of green fruit recognition using intelligent agricultural ***,FCOS-LSC can be used to improve the robustness and generalization of the green fruit detection models.

关键词： connected designing weights

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Review on flexible perovskite photodetector:processing and

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Frontiers of Mechanical engineering 2023年第2期18卷 1-31页

作者： Xuning ZHANG Xingyue LIU Yifan HUANG Bo SUN Zhiyong LIU Guanglan LIAO Tielin SHI State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China School of Mechanical Engineering and Electronic Information China University of Geoscience(Wuhan)Wuhan 430074China School of Aerospace Engineering Huazhong University of Science and TechnologyWuhan 430074China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen 518100China

Next-generation optoelectronics should possess lightweight and flexible characteristics,thus conforming to various types of surfaces or human skins for portable and wearable *** photodetectors as fundamental devices have been receiving increasing attention owing to their potential applications in artificial intelligence,aerospace industry,and wise information technology of 120,among which perovskite is a promising candidate as the light-harvesting material for its outstanding optical and electrical properties,remarkable mechanical flexibility,low-cost and low-temperature processing *** date,most of the reports have demonstrated the fabrication methods of the perovskite materials,materials engineering,applications in solar cells,light-emitting diodes,lasers,and photodetectors,strategies for device performance enhancement,few can be seen with a focus on the processing strategies of perovskite-based flexible photodetectors,which we will give a comprehensive summary,*** begin with,a brief introduction to the fabrication methods of perovskite(solution and vapor-based methods),device configurations(photovoltaic,photoconductor,and phototransistor),and performance parameters of the perovskite-based photodetectors are first ***,processing strategies for photodetectors are presented following,including flexible substrates(i.e.,polymer,carbon cloth,fiber,paper,etc.),soft electrodes(i.e.,metal-based conductive networks,carbon-based conductive materials,and two-dimensional(2D)conductive materials,etc.),conformal encapsulation(single-layer and multilayer stacked encapsulation),low-dimensional perovskites(0D,1D,and 2D nanostructures),and elaborate device *** applications of perovskite-based flexible photodetectors such as optical communication,image sensing,and health monitoring are further exhibited to learn the flexible photodetectors on a deeper *** and future research directions of perovskite-based fl

关键词： photodetector perovskite flexible processing application

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Modulating low-frequency tribocatalytic performance through defects in uni-doped and bi-doped SrTiO_(3)

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Journal of Advanced Ceramics 2024年第8期13卷 1153-1163页

作者： Yjing Xu Yingzhi Meng Xu Xiang Qing Tang Hongfang Zhang Lajun Liu Ju Gao Bo Xu Renhong Liang Longlong Shu Yanmin Jia Wanping Chen School of Physical Science and Technology Suzhou University of Science and TechnologySuzhou 215009China College of Materials Science and Engineering Guilin University of TechnologyGuilin 541004China Key Laboratory of Advanced Electrode Materials for Novel Solar Cells for Petroleum and Chemical Industry of China Suzhou University of Science and TechnologySuzhou 215009China School of Science and Key Laboratory of Biomedical Functional Materials China Pharmaceutical UniversityNanjing 211198China School of Physics and Materials Science Guangzhou UniversityGuangzhou 510006China School of Physics and Materials Science Nanchang UniversityNanchang 330031China School of Physics and Information Technology Shaanxi Normal UniversityXi'an 710062China School of Physics and Technology Wuhan UniversityWuhan 430072China

Triboelectrification,a process that transforms mechanical energy into electrical energy through friction,holds promise for eco-friendly wastewater *** study delves into the enhancement of tribocatalytic dye degradation using SrTiO_(3),a material notable for its non-piezoelectric and centrosymmetric *** synthesis of uni-and bi-doped SrTiOs particles,achieved through a solid-state reaction at 100℃,results in a high-purity cubic perovskite *** with rhodium(Rh)and carbon(C)causes crystal lattice contraction,internal stress,and significant oxygen *** changes notably improve tribocatalytic efficiency under solar irradiation,with Rh-doped SrTiO_(3) demonstrating an impressive degradation rate of approximately 88% for Rhodamine B(RhB),along with reaction rate constants near 0.9 h^(-1) at 554 nm and a noticeable *** study highlights that defects introduced by doping are integral to this process,boosting catalytic activity through energy state modification and enhancing surface redox radical ***,these defects are instrumental in generating a flexoelectric field,which markedly influences the separation of electron-hole pairs under solar *** findings illuminate the complex interplay between material composition,defect states,and environmental conditions,paving the way for advanced strategies in environmental remediation through optimized tribocatalytic activity.

关键词： tribocatalysis SrTiO_(3)(STO) doping-induced defects blueshift flexoelectric field

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